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All Journal JFMR (Journal of Fisheries and Marine Research) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Islamic Education Journal (ISEDU)
Hidayati, Nurin
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Model Pembelajaran Gamifikasi dalam Meningkatkan Motivasi Belajar Siswa Melalui Teknologi: Gamification Learning Model to Increase Student Motivation through Technology Fajar Ayu, Amilia; Puspitasari, Asih; Hidayati, Nurin; Fitra Andikos, Adi
ISEDU : Islamic Education Journal Vol. 2 No. 2 (2024): DESEMBER
Publisher : CV. Kalimasada Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59966/isedu.v2i2.1270

Abstract

This piece falls under the category of scholarly writing. It is a review of the literature, a type of scientific investigation that focuses on a particular subject. One of the ideas in e-learning is gamification. In the English language, it is frequently called "Gamification." Gamification is the process of using game mechanics and strategies to tackle problems outside of games. A key element in raising the standard of education is student motivation. Technology can be used as a tool to create a more dynamic and engaging learning environment in an effort to increase student motivation. The use of game mechanics and components to improve learning outcomes and motivation is known as "gamification" in education.
Pelatihan Tata Cara Membatik Tema Ekosistem Mangrove bagi Pengelola Wisata Alam Cisiu: Training on Mangrove Ecosystem Theme Batik for Natural Tourism Managers Fuad, Mochamad Arif Zainul; Harlyan, Ledhyane Ika; Purwanti, Pudji; Hidayati, Nurin; Rahmawati, Andira; Masdian, Nuril Haq Bilqishima; Prasetio, Rachmat Ramadhan; Putra, Valeryan Ramana; Rahmanissa, Aulia Intan
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 10 No. 5 (2025): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v10i5.8896

Abstract

The sustainable management of mangrove ecotourism requires generating additional income for its managers. One potential strategy is batik training using mangrove ecosystem motifs. On September 15, 2024, a batik training session was conducted for tour guides and managers of the Mangrove Cisiu Eco-Education Park, located in Pangkah Kulon Village, Gresik. The event was attended by 10 participants and was part of the Community Partnership Program (PKM) titled "Empowering Mangrove Managers through Eco-tourism Package Programs as Income Generating for the Sustainability of Mangrove Edupark Management on Cisiu Island", funded by DRTPM Kemendikbudristek. The training was led by Ms. Maria Cecilia, owner of Sanggar Lembayung Batik, who has extensive experience in teaching batik to various communities. Participants learned the basic techniques of batik-making, featuring motifs inspired by the mangrove ecosystem, such as Glodong fish, crabs, and mangrove trees. The training included canting techniques, wax application, and dyeing with synthetic batik dyes. In addition to technical skills, participants gained insight into the potential of batik as a creative economic product that can serve as an additional income source for ecotourism managers. This training aims to support the economic sustainability of the Mangrove Edupark Cisiu by developing high-value batik products, thus contributing to the preservation of the mangrove ecosystem through enhanced livelihoods for the local community.
PEMODELAN DAN ANALISIS PERUBAHAN GARIS PANTAI DI KABUPATEN SITUBONDO, JAWA TIMUR Fuad, M. Arif Zainul; Fajari, Annisa Kusuma; Hidayati, Nurin
JFMR (Journal of Fisheries and Marine Research) Vol. 5 No. 2 (2021): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2021.005.02.19

Abstract

Pesisir Kabupaten Situbondo yang terletak di pantai utara Jawa diduga cenderung mengalami akresi. Akan tetapi terdapat beberapa daerah di Situbondo yang rawan abrasi, seperti daerah Banyuglugur dan Besuki. Kecamatan Banyuglugur, Besuki, Mlandingan, dan Suboh merupakan daerah pesisir yang padat pemukiman dan rawan terhadap perubahan. Oleh sebab itu dilakukan prediksi perubahan garis pantai menggunakan one-line model agar dapat meminimalisir dampak yang akan terjadi. Data utama untuk memodelkan prediksi garis pantai adalah  koordinat garis pantai, kemiringan pantai, dan gelombang. Dilakukan perhitungan transpor sedimen menggunakan rumus CERC untuk mengetahui erosi maupun akresi. Kemudian didapat perubahan garis pantai berdasarkan waktu yang ditentukan. Berdasarkan hasil prediksi menggunakan one-line model, terdapat daerah di pesisir bagian barat Kabupaten Situbondo yang diprediksi mengalami erosi dan akresi. Erosi terjadi di lokasi Pantai Tampora, pemukiman Banyuglugur, tambak Kecamatan Suboh, dan  tanah kosong di TPI Mlandingan. Akresi akan dominan terjadi di lokasi mangrove Kecamatan Banyuglugur, muara Sungai Lobawang, muara Sungai Deluang, Pantai Dubibir, mangrove Kecamatan Suboh, dan muara Sungai Gardu Rusak. Pada lokasi yang mengalami garis pantai mundur, pola transpor sedimennya termasuk dalam kategori erosion. Sedangkan area yang mengalami garis pantai maju memiliki pola transpor yang termasuk dalam kategori transport as bed load. Secara kseluruhan, area penelitian mengalami akresi dengan laju akresi sebesar 0,217 m/tahun.
Analisis Akurasi Data Batimetri Single Beam Echosounder System (SBES) dan Satellite Derived Bathymetry (SDB) (Studi Kasus Perairan Kabupaten Cilacap, Jawa Tengah): Accuracy Analysis of Single Beam Echosounder System (SBES) and Satellite Derived Bathymetry (SDB) Data (Cased Study the Waters of Cilacap Regency, Central Java) Setyawan, Fahreza Okta; Rahman, Alham Danendra; Hidayati, Nurin; Fuad, Mochamad Arif Zainul; Semedi, Bambang; Setyoningrum, Desy
JFMR-Journal of Fisheries and Marine Research Vol. 10 No. 1 (2026): JFMR on March
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2026.010.01.4

Abstract

Hidrografi dan batimetri menyediakan informasi kedalaman dan bentuk dasar perairan yang sangat penting bagi navigasi, perencanaan pelabuhan, rekayasa pantai, dan tata ruang laut, terutama pada perairan dinamis dan keruh seperti Kabupaten Cilacap yang berbatasan langsung dengan Samudera Hindia. Penelitian ini bertujuan menganalisis akurasi data batimetri Satellite Derived Bathymetry (SDB) berbasis citra PlanetScope beresolusi tinggi dan membandingkannya dengan hasil pemeruman Single Beam Echosounder System (SBES). Data SBES dikumpulkan menggunakan Garmin 585 C, sedangkan kedalaman SDB diekstraksi dengan algoritma machine learning Generalized Additive Model (GAM). Data dibagi 75% untuk training dan 25% untuk testing, dan kinerja model dinilai menggunakan koefisien determinasi (R²) dan Root Mean Square Error (RMSE). Pengolahan data didukung perangkat lunak SIG dan penginderaan jauh seperti ArcMap, SNAP, ENVI, Global Mapper, RStudio, dan Surfer. Hasil menunjukkan SBES memiliki akurasi tinggi dan tetap menjadi rujukan utama pemetaan dasar perairan Cilacap. Sebaliknya, model SDB–GAM menghasilkan R² sebesar 0,35 dan RMSE 2,80 sehingga belum mampu merepresentasikan variasi kedalaman pada perairan. Nilai ini rendah karena perairan Cilacap yang keruh serta keberadaan sunglint pada citra menyebabkan distorsi reflektansi sehingga kedalaman hasil SDB sulit merepresentasikan variasi kedalaman aktual. Oleh karena itu, SDB – GAM belum direkomendasikan untuk pemetaan operasional di perairan keruh seperti Cilacap tanpa koreksi glint dan peningkatan strategi pemodelan, serta lebih tepat digunakan sebagai pemetaan awal pada kondisi perairan yang lebih jernih dan kedalaman terbatas.   Hydrography and bathymetry provide information on water depth and seabed morphology that is crucial for navigation, port planning, coastal engineering, and marine spatial planning, especially in dynamic and turbid waters such as Cilacap Regency, which borders directly with the Indian Ocean. This study aims to analyze the accuracy of bathymetric data Satellite Derived Bathymetry (SDB) derived from high-resolution PlanetScope imagery and compare it with obtained from Single Beam Echosounder System (SBES) sounding. SBES data were collected using a Garmin 585 C, while SDB depths were extracted using the Generalized Additive Model (GAM) machine learning algorithm. Data were split into 75% for training and 25% for testing, and model performance was evaluated using the coefficient of determination (R²) and Root Mean Square Error (RMSE). Data processing was supported by GIS and remote sensing software such as ArcMap, SNAP, ENVI, Global Mapper, RStudio, and Surfer. The results show that SBES provides high accuracy and remains the primary reference for seabed mapping in Cilacap waters. Conversely, the SDB–GAM model produces an R² of 0.35 and an RMSE of 2.80, indicating that it has not yet adequately represented depth variability in waters. This value is low because the murky waters of Cilacap and the presence of sunglint in the image cause reflectance distortion, making it difficult for the SDB results to represent actual depth variatons. Therefore, SDB-GAM is not yet recommended for operational mapping in murky waters such as Cilacap without glint correction and improved modeling strategies, and is more appropriately used for initial mapping in clearer waters and limited depths.
Co-Authors Bambang Semedi Fajar Ayu, Amilia Fajari, Annisa Kusuma Fitra Andikos, Adi Fuad, M. Arif Zainul Fuad, Mochamad Arif Zainul Ledhyane Ika Harlyan Masdian, Nuril Haq Bilqishima Prasetio, Rachmat Ramadhan Pudji Purwanti Puspitasari, Asih Putra, Valeryan Ramana Rahman, Alham Danendra Rahmanissa, Aulia Intan Rahmawati, Andira Setyawan, Fahreza Okta Setyoningrum, Desy